Al-Furat Journal of Innovations in Management Sciences

The goal of this paper is to compare the performance of the statistical and machine learning classification methods in diagnosing the death of liver cancer patients based on demographic characteristics, risk factors, and medical interventions. For this purpose, five methods; include random tree, C4.5, random forest, support vector machine (SVM) and logistic regression, all of which are supervised methods, were selected. The data used in this research are the real data of 165 patients diagnosed with liver cancer in a hospital in Portugal. The aim variable is the patient\\\\'s death during the trial period, and the aforementioned group was monitored for a year. There are twenty-six qualitative and twenty-three quantitative variables in this diverse dataset. In total, 10.22% of the dataset is missing data, and just eight patients have full information in every field (4.85%). Additionally, there is some class disparity (63 cases classified as \\\\"Dead\\\\" and 102 as \\\\"Alive\\\\"). With 73.33% accurate detection, the SVM approach was found to be the most effective approach. After that, the random forest method with 71.52% had a more correct identification ratio than the others. The treesC4.5 method had the lowest correct diagnosis with 58.18%. Although, based on the ROC Area index, the random forest method performed better (with an area under the curve = 0.789) than the SVM method (with an area under the curve = 0.711). In total, SVM and random forest methods worked with a large difference compared to others in diagnosing the death of patients with liver cancer

The Poisson regression model is one of the most important logarithmic linear regression models, and it is the tool through which the response variable is modeled when the values of that variable are in the form of countable values. Like other regression models, the model may contain many explantory variables, which negatively affects the accuracy of the model and its simplicity in interpreting the results. This study aims to use the Golden Jackal algorithm and compare it with other methods in selecting variables in the Poisson regression model using simulation and real data. The Monte-Carlo method was used in the simulation to generate data that follow the Poisson regression model according to different factors such as sample size and the number of explantory variables. Two aspects of the performance evaluation of the methods used were relied upon: the first is to evaluate the accuracy of prediction and the second is to evaluate the selection of variables as a criterion for comparison. The simulation results showed the superiority of the Golden Jackal algorithm compared to other variable selection methods. In addition, the application was carried out on real data collected from patients with chronic kidney disease who are treated with continuous hemodialysis, and the patients' condition was diagnosed by specialist doctors in cooperation with Ibn Sina Teaching Hospital - Artificial Kidney Unit.

Evolution has created an environment that needs standards to keep pace with its constant change. This led to changes in the accounting measurement which in turn affected the value of earnings per share. Therefore, the question of the study problem is focused on: Is there an effect of the fair value on the appropriateness of the book value of the stock?
This study aim to know the effect of fair value on the Relevance book value per share for the research sample bank listed in the Iraq Stock Exchange.
The importance of the study is embodied in the importance of accounting information for users of the financial statements in making their decisions and relying on them in evaluating the performance of the economic unit, as well as the interest of standard-setters and researchers in the Relevance of earnings per share as it is one of the means of evaluating the quality of accounting information.
To achieve the goal of the research, the descriptive analytical approach was adopted in the practical aspect through statistical analysis using the (SPSS) program to measure the impact of fair value on the Relevance of the book value of the stock.
There are differences in the impact between measurement and fair value disclosure on the explanatory power of accounting figures
The research reached some recommendations, the most important of which are: Pay more attention to the disclosure of fair value and strive to adhere to the application of international financial standards that contribute to achieving the quality of information whose effects are positively reflected on future performance.

The academic performance of university students is influenced by various factors, including the department in which they are enrolled. Understanding these influences is essential for developing effective educational strategies and improving student outcomes. This study focuses on first-year students in the Accounting and Statistics and informatics departments at Sulaimani University, examining how the type of department affects their academic performance in ICT and Principles of Statistics classes. By utilizing the Multivariate Analysis of Variance (MANOVA) approach, this research aims to identify significant differences and underlying patterns in academic achievements between these two departments. The insights gained from this study can inform targeted interventions and support mechanisms to enhance educational effectiveness. Results showed that Statistics and Informatics students outperformed accounting students in both ICT and Principles of Statistics courses, with mean scores of 65.75 vs. 58.80 in ICT and 76.20 vs. 71.70 in Statistics, respectively. Box's test indicated significant differences in covariance matrices, suggesting that results should be interpreted with caution. Multivariate tests confirmed a strong departmental effect on performance, with partial eta squared values indicating substantial variance explained by the department. Levene's test showed unequal error variances for ICT but not for Statistics. Between-subjects effects analysis revealed highly significant differences between departments, with 93.6% and 97.3% of the variance in ICT and Statistics scores, respectively, explained by the department. Parameter estimates further highlighted the higher performance of Statistics and Informatics students. Overall, the findings emphasize significant academic disparities favoring the Statistics department

The research aims to define the concept of reporting on financial performance and its main dimensions. It also shows the role of the financial reporting standard IFRS6 in improving financial performance reporting through the presentation and analysis of financial analysis indicators to help the management of oil companies identify the reality of their financial status and activities and the status of their cash flows. As for the importance of the study, it lies in the importance of reporting on the financial performance of investment oil companies. To achieve the objectives of the study, the researcher adopted the analytical approach in the practical aspect through the method of financial analysis to report on the financial performance by the company's IFRS6 standard (the research sample) in a way that contributes to providing the decision-maker with the necessary Information to rationalize the decision.

The research aims to understand the impact of tax policies on the environment and the economy and to provide practical recommendations for designing future tax policies that promote environmental conservation and achieve sustainable development. By evaluating the tax in a view of recent economic developments, and that tax policies play an effective role in promoting environmental sustainability, encouraging companies to adopt sustainable environmental practices by providing tax incentives for environmental initiatives. Environmental taxes direct economic behavior towards the sustainable use of resources and promote the transition to environmentally friendly technologies and practices by imposing taxes on polluters and unsustainable practices. The researchers used a questionnaire form to sample academics in the city of Sulaymaniyah. 40 questionnaires were distributed electronically and were valid for analysis. Several results are confirmed, the most important of which is that tax procedures such as environmental taxes encourage international cooperation in the field of environmental conservation and promoting sustainable development. As a result, it is recommended there is a need to pay attention to developing effective mechanisms for assessing the environmental impact of tax policies, including estimating the impact on carbon emissions and consumption of natural resources.

The research aims to identify and measure market risks that have been referred to within the international financial reporting standards in preparation for disclosure in the financial statements and its impact on any of the income and balance sheet elements to help users, chiefly investors and creditors, improve their knowledge of the financial position of companies and take the right decision.
In order to achieve the objective of the research, the researchers adopted the deductive approach for literature review by collecting previous sources and studies. Through the applied study the researchers used the data of trading prices in the Iraq Stock Exchange (of the Baghdad Soft Drinks Company) for 2019 to measure the market risk referred to in IFRSs by covariance - covariance method for estimating the value at risk to show how the Company's equity and annual profits affected as a result of its exposure to market risks.
The research concluded that there is no unified methodology for measuring the risks referred to by IFRSs. So, the most important recommendations is for the International Accounting Standards Board to provide a unified methodology for measuring risks and obligating all economic units that apply IFRS to submit their financial data, including information for measuring risks exposed to, for enhancing the qualitative characteristics of accounting information in the service of economic decision-makers